Hello everyone, I have a data frame (tt), see below (I only show 2 genes, actually I have a lot):
group gene1 gene2 Control 28.9776 9.9355 Control 28.9499 10.0997 Control 29.5468 14.2995 Control 29.5246 13.9561 Test1 29.1864 9.7718 Test1 29.2048 10.0388 Test1 34.9563 11.9509 Test1 34.9464 11.8909 Test2 36.9566 14.5316 Test2 37.1309 14.5188 Test2 36.1017 29.5468 Test2 36.0883 29.5246 I'd like to calculate p values: Test1 vs Control and Test2 vs Control respectively for Gene1. Similar calculate performed for Gene2. I tried: sapply(levels(fac), function(x) t.test(tt1$gene1, tt$gene1[which(fac==x)])$p.value) # I don't really understand how it works, I copied from genefilter. where: fac=as.factor(tt$group) It seemed to work for first column. I don't know how to use apply() to make it work on rest of column because I used tt$gene1 specifically. Or whatever method that works Thank you in advance. Junyu [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.